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A/B Website Testing

A/B testing is a scientific comparison of two versions of a web page to see which one has higher conversion rates. The goal of A/B testing is coming up with changes on a web page to increase the revenue generated from existing visitors. It is an effective way of boosting the conversion rate without affecting other sections of your site.

Heatmapping and Google Analytics

It is recommended that you start testing on the worst performing web pages as it is highly likely that these are the areas where most prospective revenue is lost. Google Analytics helps analyse your site’s conversion funnel and user journeys to determine the pages that have the worst conversion rates. The heatmaps generated from Google Analytics helps in identifying the web pages that are not performing well, and this pinpoints the areas to start the A/B testing.

A/B testing: Process

Creating an actionable, testable hypothesis

Creating a testable hypothesis is a vital step as it helps in predicting what is true and false using data gained through testing. This is what makes A/B testing scientific. An example of a testable hypothesis is enlarging the ‘buy now’ product button to boost the conversion rates, or altering the working of the email signup popup to increase the users signing up for your weekly mailing list. These predictions are tested against the original version of your site to determine if they are true or false.

Running A/B testing

Conducting an effective A/B test is very critical. A Visual Website Optimiser is used to make a few alterations to a website, and then show the test version or original version randomly to the same visitors. If tests are carried out properly, they won’t have an adverse effect on your website performance. One way of doing this is through cannibalising the tested web pages to the original URL and redirecting it with a 302 to ensure the organic search rank isn’t affected negatively.

Analyse the test results

After testing is done, the results are properly analysed to determine if the hypothesis recorded positive or negative results. Statistically, results are also considered, not just minor changes. A positive result means that the change is beneficial and should be permanently implemented. A negative outcome helps you know what visitors are looking for and this can come in handy when conducting the next test.

Implementation and Review

The most crucial thing in this stage is understanding the results, whether positive or negative and implementing these lessons in the future. This enables the process to be more productive and for similar gains to be made on your site. A/B testing is a recurrent process that is designed to keep increasing your conversion rates. These tests are used to continually boost your website’s conversions and provide a significant improvement to the number of your sales.

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A/B testing vs. Multivariate

A/B testing involves extensive experiments which test variations of multiple elements, and comprise of more than 20 simultaneous test web pages. A/B tests are the fastest way of refining a specific element, whereas multivariate testing enables you to view what features have the most significant impact when altered.

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